Supplementary Materials of the Article A Semantic Approach to Understanding GDPR Fines: From Text to Compliance Insights

Supplementary Materials as follow: stop_words.csv: the custom stop words list used in the final STM run synonyms.csv: the custom synonyms substitution list in the final STM run topic_general_Proportion_Topic_Table.csv: list of estimated topic proportion in the corpus with the expected number of documents containing the topic Topic_Words.csv: complete list of highest 15 tokens (uni-, bi-, trigrams) for each topic with associated value of FREX, Lift and Score.